CODEWITHSUNDEEP
r
outis
outis

Reputation: 831

How to convert survey answers in data frame to numbers in order to average results

I have a data frame with survey results that looks like this:

          Q1         Q2       Q3
1      Agree No opinion Disagree
2 No opinion No opinion Disagree
3      Agree            Disagree

How can I convert the survey responses into numbers so that I can get the mean response for each question? I can use gsub to substitute numeric values for each text answer in each column, but there must be a better way.

> str(x)
'data.frame':   3 obs. of  3 variables:
 $ Q1: Factor w/ 2 levels "Agree","No opinion": 1 2 1
 $ Q2: Factor w/ 2 levels "","No opinion": 2 2 1
 $ Q3: Factor w/ 1 level "Disagree": 1 1 1

Upvotes: 0

Views: 2304

Answers (2)

Simon O'Hanlon
Simon O'Hanlon

Reputation: 59970

I must be misunderstanding what you want, but since you have categorical variables in a data.frame can't you just use summary on it?

#Example
q1 <- sample( c("Agree" , "No opinion" ) , 10 , replace = TRUE )
q2 <- sample( c(" " , "No opinion" ) , 10 , replace = TRUE )
q3 <- sample( c("Agree" , "Disagree" ) , 10 , replace = TRUE )

x <- data.frame( q1 , q2 , q3 )

summary(x)
  q1             q2           q3   
  Agree     :4   ,         :4   Agree   :5  
  No opinion:6   No opinion:6   Disagree:5

Upvotes: 0

Theodore Lytras
Theodore Lytras

Reputation: 3965

OK, it is clear now.

I would convert each column to character, then to factor (with common levels), then to integer:

sapply(data, function(x) as.integer(factor(as.character(x), levels=c("Agree", "No opinion", "Disagree"))))

Upvotes: 5

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